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Record W2903264552 · doi:10.3390/children5120159

Exploring the Effect of Perceptions on Children’s Physical Activity in Varying Geographic Contexts: Using a Structural Equation Modelling Approach to Examine a Cross-Sectional Dataset

2018· article· en· W2903264552 on OpenAlexafffundabout
Leah G. Taylor, Andrew Clark, Piotr Wilk, Brenton Button, Jason Gilliland

Bibliographic record

VenueChildren · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsChildren’s Health Research InstituteWestern University
FundersCanadian Institutes of Health ResearchSocial Sciences and Humanities Research Council of CanadaHeart and Stroke Foundation of CanadaChildren's Health Research Institute
KeywordsStructural equation modelingPerceptionCross-sectional studyPhysical activityPsychologyEconometricsMathematicsStatisticsMedicine

Abstract

fetched live from OpenAlex

Most Canadian children are not meeting the recommended 60 min of moderate-to-vigorous physical activity per day. Research suggests that children's perceptions of their environment have an influence on their physical activity behaviours, but there is a lack of generalizability among previous work. The purpose of this study was to assess the mediating effect of children's perceptions of barriers to physical activity on the relationship between their environments and their level of moderate-to-vigorous physical activity (measured with accelerometers). Structural equation modelling stratified by gender was used to assess the research objective in a sample of 546 participants aged 8⁻14 years old from Northwestern and Southwestern Ontario, Canada. In both models stratified by gender, perceptions of barriers did not significantly mediate the relationship between urbanicity and physical activity. Independent of all other factors, there was no significant relationship between urbanicity and physical activity in girls, but there was in boys. These results offer insight into potential processes by which perceptions impact physical activity and provide initial information to further our understanding of the behavioural aspects of physical activity through multiple levels of analysis. Researchers must continue to improve efforts for quantifying the experience of children's daily activity contexts.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.116
GPT teacher head0.354
Teacher spread0.238 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations16
Published2018
Admission routes3
Has abstractyes

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